Table 5. Performance comparisons on three datasets in terms of Precision, Recall and F1 score.

Data sets	NYT			Yelp			Tweet
Method	Precision	Recall	F1	Precision	Recall	F1	Precision	Recall	F1
Pattern [7]	0.4576	0.2247	0.3014	0.3790	0.1354	0.1996	0.2107	0.2368	0.2230
FIGER [12]	0.8668	0.8964	0.8814	0.5010	0.1237	0.1983	0.7354	0.1951	0.3084
SemTagger [9]	0.8667	0.2658	0.4069	0.3769	0.2440	0.2963	0.4225	0.1632	0.2355
APOLLO [22]	0.9257	0.6972	0.7954	0.3534	0.2366	0.2834	0.1471	0.2635	0.1883
NNPLB [11]	0.7487	0.5538	0.6367	0.4248	0.6397	0.5106	0.3327	0.1951	0.2459
ClusType-NoClus	0.9130	0.8685	0.8902	0.7629	0.7581	0.7605	0.3466	0.4920	0.4067
ClusType-NoWm	0.9244	0.9015	0.9128	0.7812	0.7634	0.7722	0.3539	0.5434	0.4286
ClusType-TwoStep	0.9257	0.9033	0.9143	0.8025	0.7629	0.7821	0.3748	0.5230	0.4367
ClusType	0.9550	0.9243	0.9394	0.8333	0.7849	0.8084	0.3956	0.5230	0.4505